AI Engineer - FDE (Forward Deployed Engineer) - Public Sector

Sorry, this job was removed at 12:23 a.m. (UTC) on Tuesday, Feb 03, 2026
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3 Locations
In-Office or Remote
181K-248K Annually
Big Data • Machine Learning • Software • Analytics • Big Data Analytics
The Role

CSQ326R87
PLEASE NOTE: This position requires eligibility to work in the United States and the ability to obtain and maintain a U.S. Government security clearance at the Secret level or higher, as required by applicable federal law and contract terms. Due to specific federal contract requirements and client site access obligations for this role, U.S. citizenship is a condition of employment. The role is based in the Washington, D.C., Maryland, or Virginia metropolitan area to support periodic on‑site work and client collaboration. Candidates with an active Secret clearance or higher are strongly encouraged to apply. 

The AI Forward Deployed Engineering (AI FDE) team is a highly specialized customer-facing AI team at Databricks. We deliver professional services engagements to help our customers build and productionize first-of-its-kind AI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams. We view our team as an ensemble: we look for individuals with strong, unique specializations to improve the overall strength of the team. This team is the right fit for you if you love working with customers, teammates, and fueling your curiosity for the latest trends in GenAI, LLMOps, and ML more broadly. This role can be remote.

The impact you will have:

  • Develop cutting-edge GenAI solutions, incorporating the latest techniques from our Mosaic AI Research to solve customer problems
  • Own production rollouts of consumer and internally facing GenAI applications
  • Serve as a trusted technical advisor to customers across a variety of domains
  • Present at conferences such as Data + AI Summit, recognized as a thought leader internally and externally
  • Collaborate cross-functionally with the product and engineering teams to influence priorities and shape the product roadmap

What we look for:

  • Experience building GenAI applications, including RAG, multi-agent systems, Text2SQL, fine-tuning, etc., with tools such as HuggingFace, LangChain, and DSPy
  • Expertise in deploying production-grade GenAI applications, including evaluation and optimizations 
  • Extensive years of hands-on industry data science experience, leveraging common machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.)
  • Experience building production-grade machine learning deployments on AWS, Azure, or GCP
  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
  • Passion for collaboration, life-long learning, and driving business value through AI
  • [Preferred] Experience using the Databricks Intelligence Platform and Apache Spark™ to process large-scale distributed datasets

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.


Zone 2 Pay Range
$180,656—$248,360 USD

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.


Zone 3 Pay Range
$180,656—$248,360 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks. 

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

Databricks Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.

  • Healthcare Strength — Healthcare coverage is described as comprehensive, including medical, dental, and vision for employees and dependents, plus dedicated mental-health resources and an EAP. Wellness and gym reimbursements further support wellbeing.
  • Equity Value & Accessibility — Equity grants (RSUs/stock options) are highlighted as a major part of compensation and are often viewed as attractive. Occasional tender-offer liquidity and performance bonuses reinforce total rewards.
  • Parental & Family Support — Paid parental leave, fertility benefits, and subsidized backup dependent care are emphasized. Family medical leave and caregiver support also feature in the package.

Databricks Insights

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The Company
HQ: San Francisco, CA
2,200 Employees
Year Founded: 2013

What We Do

As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.

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